This assessment demonstrates enhanced forecasting accuracy of solar power in smart grids, suggesting AI models are vital for effective energy management.
Key Points
HAELNet achieved the lowest MAPE values for daily solar power generation and grid-connected generation.
Hybrid models like HAELNet and HCLNet were compared, with HAELNet outperforming in error metrics.
LSTMNet showed superior performance in forecasting solar energy compared to traditional methods.
The study highlights the importance of machine learning in advancing renewable energy sustainability.